A device to investigate the axial strain dependence of the critical current density in superconductors

We have developed an instrument to study the behavior of the critical current density (J(c)) in superconducting wires and tapes as a function of field (mu(0)H), temperature (T), and axial applied strain (epsilon(a)). The apparatus is an improvement of similar devices that have been successfully used in our institute for over a decade. It encompasses specific advantages such as a simple sample layout, a well defined and homogeneous strain application, the possibility of investigating large compressive strains and the option of simple temperature variation, while improving the main drawback in our previous systems by increasing the investigated sample length by approximately a factor of 10. The increase in length is achieved via a design change from a straight beam section to an initially curved beam, placed perpendicular to the applied field axis in the limited diameter of a high field magnet bore. This article describes in detail the mechanical design of the device and its calibrations. Additionally initial J(c)(epsilon(a)) data, measured at liquid helium temperature, are presented for a bronze processed and for a powder-in-tube Nb3Sn superconducting wire. Comparisons are made with earlier characterizations, indicating consistent behavior of the instrument. The improved voltage resolution, resulting from the increased sample length, enables J(c) determinations at an electric field criterion E-c=10 muV/m, which is substantially lower than a criterion of E-c=100 muV/m which was possible in our previous systems. (C) 2004 American Institute of Physics.

Predictive Current Control of Doubly Fed Induction Generators

This paper presents a predictive current control strategy for doubly-fed induction generators (DFIG). The method predicts the DFIG’s rotor current variations in the synchronous reference frame fixed to the stator flux within a fixed sampling period. This is then used to directly calculate the required rotor voltage to eliminate the current errors at the end of the following sampling period. Space vector modulation is used to generate the required switching pulses within the fixed sampling period. The impact of sampling delay on the accuracy of the sampled rotor current is analyzed and detailed compensation methods are proposed to improve the current control accuracy and system stability. Experimental results for a 1.5 kW DFIG system illustrate the effectiveness and robustness of the proposed control strategy during rotor current steps and rotating speed variation. Tests during negative sequence current injection further demonstrate the excellent dynamic performance of the proposed PCC method.

A Kernel Interleaved Scheduling Method for Streaming Applications on Soft-core Vector Processors

Massively parallel networks of highly efficient, high performance Single Instruction Multiple Data (SIMD) processors have been shown to enable FPGA-based implementation of real-time signal processing applications with performance and
cost comparable to dedicated hardware architectures. This is achieved by exploiting simple datapath units with deep processing pipelines. However, these architectures are highly susceptible to pipeline bubbles resulting from data and control hazards; the only way to mitigate against these is manual interleaving of
application tasks on each datapath, since no suitable automated interleaving approach exists. In this paper we describe a new automated integrated mapping/scheduling approach to map algorithm tasks to processors and a new low-complexity list scheduling technique to generate the interleaved schedules. When applied to a spatial Fixed-Complexity Sphere Decoding (FSD) detector
for next-generation Multiple-Input Multiple-Output (MIMO) systems, the resulting schedules achieve real-time performance for IEEE 802.11n systems on a network of 16-way SIMD processors on FPGA, enable better performance/complexity balance than current approaches and produce results comparable to handcrafted implementations.

siRNA Technology in Kidney Transplantation: Current Status and Future Potential

Kidney transplantation is one of the most common transplantation operations in the world, accounting for up to 50 % of all transplantation surgeries. To curtail the damage to transplanted organs that is caused by ischemia-reperfusion injury and the recipient's immune system, small interfering RNA (siRNA) technology is being explored. Importantly, the kidney as a whole is a preferential site for non-specific systemic delivery of siRNA. To date, most attempts at siRNA-based therapy for transplantation-related conditions have remained at the in vitro stage, with only a few of them being advanced into animal models. Hydrodynamic intravenous injection of naked or carrier-bound siRNAs is currently the most common route for delivery of therapeutic constructs. To our knowledge, no systematic screens for siRNA targets most relevant for kidney transplantation have been attempted so far. A majority of researchers have arrived at one or another target of interest by analyzing current literature that dissects pathological processes taking place in transplanted organs. A majority of the genes that make up the list of 53 siRNA targets that have been tested in transplantation-related models so far belong to either apoptosis- or immune rejection-centered networks. There is an opportunity for therapeutic siRNA combinations that may be delivered within the same delivery vector or injected at the same time and, by targeting more than one pathway, or by hitting the same pathways within two different key points, will augment the effects of each other.

A Fast Algorithm for Sparse Support Vector Machines for Mobile Computing Applications

This research presents a fast algorithm for projected support vector machines (PSVM) by selecting a basis vector set (BVS) for the kernel-induced feature space, the training points are projected onto the subspace spanned by the selected BVS. A standard linear support vector machine (SVM) is then produced in the subspace with the projected training points. As the dimension of the subspace is determined by the size of the selected basis vector set, the size of the produced SVM expansion can be specified. A two-stage algorithm is derived which selects and refines the basis vector set achieving a locally optimal model. The model expansion coefficients and bias are updated recursively for increase and decrease in the basis set and support vector set. The condition for a point to be classed as outside the current basis vector and selected as a new basis vector is derived and embedded in the recursive procedure. This guarantees the linear independence of the produced basis set. The proposed algorithm is tested and compared with an existing sparse primal SVM (SpSVM) and a standard SVM (LibSVM) on seven public benchmark classification problems. Our new algorithm is designed for use in the application area of human activity recognition using smart devices and embedded sensors where their sometimes limited memory and processing resources must be exploited to the full and the more robust and accurate the classification the more satisfied the user. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm. This work builds upon a previously published algorithm specifically created for activity recognition within mobile applications for the EU Haptimap project [1]. The algorithms detailed in this paper are more memory and resource efficient making them suitable for use with bigger data sets and more easily trained SVMs.

Corneal hysteresis is correlated with reduction in axial length after trabeculectomy.

BACKGROUND: We sought to determine whether corneal biomechanical parameters are predictive of reduction in axial length after anti-metabolite trabeculectomy. METHODS: Chinese subjects undergoing trabeculectomy with mitomycin C by a single experienced surgeon underwent the following measurements: Corneal hysteresis (CH, Ocular Response Analyzer, Reichert Ophthalmic Instruments), Goldmann intra-ocular pressure (IOP), central corneal thickness (CCT) and axial length (AL, IOLMaster, Carl Zeiss Meditec, Dublin, CA) were measured pre-operatively, and AL, CH and IOP were measured 1 day and 1 week post-operatively. RESULTS: Mean age of 31 subjects was 52.0 ± 15.2 years, and 15 (48.4%) were female. The mean pre-operative IOP of 21.4 ± 9.3 mmHg was reduced to 8.2 ± 4.6 mmHg 1 day and 11.0 ± 4.4 mmHg 1 week post-operatively (p < 0.001). AL declined from 22.99 ± 0.90 to 22.76 ± 0.87 mm at 1 day and 22.74 ± 0.9 mm at 1 week; 30/31 (%) eyes had a decline in AL (p < 0.001, sign test). In multivariate linear regression models including post-operative data from 1 day and 1 week, greater decline in Goldmann IOP (p < 0.0001, greater pre-op axial length (p < 0.001) and lower pre-operative CH (p = 0.03), were all associated with greater decline in post-operative axial length. CONCLUSIONS: Eyes with lesser ability of the ocular coat to absorb energy (lower CH) had significantly greater decrease in axial length after trabeculectomy-induced IOP-lowering.